Viscosity investigations on the binary systems of (1 chcl:2 ethylene glycol) des and methanol or ethanol

Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.In this study, the viscosity behavior of two mixtures of Ethaline (1 ChCl:2 ethylene glycol) with either methanol or ethanol were investigated over the temperature range of 283.15–333.15 K at atmospheric pressure. The measured viscosities of neat Ethaline, methanol, and ethanol showed reliable agreement with the corresponding reported literature values. The mixture viscosities were modeled by an Arrhenius-like model to determine the behavior of viscosity with respect to temperature. The data were also modeled by the four well-known mixture viscosity models of Grunberg–Nissan, Jouyban–Acree, McAllister, and Preferential Solvation. All of the model results were reliable, with the Jouyban–Acree and Preferential Solvation models showing the most accurate agreement with the experimental measurements. The Jones–Dole viscosity model was also investigated for the measured viscosities, and by analyzing the results of this model, strong interactions among Ethaline and the alcohol molecules were proposed for both systems. As a final analysis, viscosity deviations of the investigated systems were calculated to study the deviations of the viscosity behaviors with respect to ideal behavior. Both systems showed negative viscosity deviations at all of the investigated temperatures, with the negative values tending towards zero, and hence more ideal behavior, with increasing temperatures. Moreover, in order to correlate the calculated viscosity deviations, the Redlich–Kister model was successfully used for both systems and at each investigated temperature.publishersversionpublishe

Group contribution and atomic contribution models for the prediction of various physical properties of deep eutectic solvents

Publisher Copyright: © 2021, The Author(s).The urgency of advancing green chemistry from labs and computers into the industries is well-known. The Deep Eutectic Solvents (DESs) are a promising category of novel green solvents which simultaneously have the best advantages of liquids and solids. Furthermore, they can be designed or engineered to have the characteristics desired for a given application. However, since they are rather new, there are no general models available to predict the properties of DESs without requiring other properties as input. This is particularly a setback when screening is required for feasibility studies, since a vast number of DESs are envisioned. For the first time, this study presents five group contribution (GC) and five atomic contribution (AC) models for densities, refractive indices, heat capacities, speeds of sound, and surface tensions of DESs. The models, developed using the most up-to-date databank of various types of DESs, simply decompose the molecular structure into a number of predefined groups or atoms. The resulting AARD% of densities, refractive indices, heat capacities, speeds of sound and surface tensions were, respectively, 1.44, 0.37, 3.26, 1.62, and 7.59% for the GC models, and 2.49, 1.03, 9.93, 4.52 and 7.80% for the AC models. Perhaps, even more importantly for designer solvents, is the predictive capability of the models, which was also shown to be highly reliable. Accordingly, very simple, yet highly accurate models are provided that are global for DESs and needless of any physical property information, making them useful predictive tools for a category of green solvents, which is only starting to show its potentials in green technology.publishersversionpublishe

A global model for the estimation of speeds of sound in deep eutectic solvents

ERC-2016-CoG 725,034 UID/QUI/50006/2019Deep eutectic solvents (DESs) are newly introduced green solvents that have attracted much attention regarding fundamentals and applications. Of the problems along the way of replacing a common solvent by a DES, is the lack of information on the thermophysical properties of DESs. This is even more accentuated by considering the dramatically growing number of DESs, being made by the combination of vast numbers of the constituting substances, and at their various molar ratios. The speed of sound is among the properties that can be used to estimate other important thermodynamic properties. In this work, a global and accurate model is proposed and used to estimate the speed of sound in 39 different DESs. This is the first general speed of sound model for DESs. The model does not require any thermodynamic properties other than the critical properties of the DESs, which are themselves calculated by group contribution methods, and in doing so, make the proposed method entirely independent of any experimental data as input. The results indicated that the average absolute relative deviation percentages (AARD%) of this model for 420 experimental data is only 5.4%. Accordingly, based on the achieved results, the proposed model can be used to predict the speeds of sound of DESs.publishersversionpublishe

Investigation of carbon dioxide solubility in various families of deep eutectic solvents by the PC-SAFT EoS

Publisher Copyright: Copyright © 2022 Parvaneh, Haghbakhsh, Duarte and Raeissi.Having been introduced in 2003, Deep Eutectic Solvents (DESs) make up a most recent category of green solvents. Due to their unique characteristics, and also their tunable physical properties, DESs have shown high potentials for use in various applications. One of the investigated applications is CO2 absorption. The thermodynamic modeling of CO2 solubility in DESs has been pursued by a number of researchers to estimate the capacity and capability of DESs for such tasks. Among the advanced equations of state (EoSs), the Perturbed Chain-Statistical Associating Fluid Theory (PC-SAFT) is a well-known EoS. In this study, the performance of the PC-SAFT EoS for estimating CO2 solubility in various DESs, within wide ranges of temperatures and pressures, was investigated. A large data bank, including 2542 CO2 solubility data in 109 various-natured DESs was developed and used for this study. This is currently the most comprehensive study in the open literature on CO2 solubility in DESs using an EoS. For modeling, the DES was considered as a pseudo-component with a 2B association scheme. CO2 was considered as both an inert and a 2B-component and the results of each association scheme were compared. Considering the very challenging task of modeling a complex hydrogen bonding mixture with gases, the results of AARD% being lower than 10% for both of the investigated association schemes of CO2, showed that PC-SAFT is a suitable model for estimating CO2 solubilities in various DESs. Also, by proposing generalized correlations to predict the PC-SAFT parameters, covering different families of DESs, the developed model provides a global technique to estimate CO2 solubilities in new and upcoming DESs, avoiding the necessity of further experimental work. This can be most valuable for screening and feasibility studies to select potential DESs from the innumerable options available.publishersversionpublishe

Deep eutectic solvent viscosity prediction by hybrid machine learning and group contribution

Funding Information: The authors wish to thank Shiraz University, University of Isfahan and Universidade Nova de Lisboa for the facilities provided. Publisher Copyright: © 2023 The Author(s)In this study, hybrid machine learning nonlinear models were developed to predict the viscosity of DESs by combining the group contribution (GC) concept with the multilayer perceptron, a well-known feedforward artificial neural network, and the Least Squares Support Vector Machine (LSSVM) algorithm. Deep Eutectic Solvents (DESs) have come to the forefront in recent years as appealing substitutes for conventional solvents. It is imperative to have a thorough grasp of the essential properties of DESs to expand the employment of these compounds in new procedures. Most frequently, one of the crucial physical properties of a DES that must be precisely determined is its viscosity. To develop the models, a dataset of 2533 viscosity data points for 305 DESs at various temperatures (from 277.15 to 373.15 K) was gathered to build the models. By using temperature, molar ratios, and functional groups as inputs, the results indicate that the suggested models can determine the viscosity of DESs with high accuracy. The models yield average absolute relative deviations below 10% and squared correlation coefficients higher than 0.98.publishersversionpublishe

Energy conservation in absorption refrigeration cycles using DES as a new generation of green absorbents

ERC-2016-CoG 725,034 UID/QUI/50006/2019Deep eutectic solvents (DESs) are emerging green solvents with very unique characteristics. Their contribution to atmospheric pollution is negligible, and they can be "designed" for desired properties. In this study, the feasibility of applying DESs (Reline, Ethaline, or Glyceline) as absorbents in absorption refrigeration cycles was investigated. The sophisticated cubic-plus-association (CPA) equation of state, considering the strong intermolecular interactions of such complex systems, was used to estimate the thermodynamic properties. At a fixed set of base case operating conditions, the coefficients of performance were calculated to be 0.705, 0.713, and 0.716 for Reline/water, Ethaline/water, and Glyceline/water systems, respectively, while the corresponding mass flow rate ratios were 33.73, 11.53, and 16.06, respectively. Furthermore, the optimum operating conditions of each system were estimated. To verify the feasibility, results were compared to literature systems, including LiBr/water and various ionic liquid/water systems. The results indicate that DES/water working fluids have the potential to be used in such cycles. Since DESs have the characteristic to be tuned (designed) to desired properties, including their solvent power and their enthalpies of absorption, much further research needs to be done to propose new DESs with higher energy efficiencies.publishersversionpublishe

Creative strategies in navigating the new normal: advancing the contributions of the ISPRS student consortium as an internatıonal organization

17 June 2021 2021 24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow, Commission V and Youth ForumNice5 July 2021 through 9 July 2021Code 174094The International Society for Photogrammetry and Remote Sensing Student Consortium (ISPRS SC) is an international student organization representing the youth in the ISPRS. The COVID-19 pandemic adversely affected students and young professionals around the world because of country-wide lockdowns and comprehensive quarantine and social distancing measures. This situation led to the implementation of distance learning and remote work. The Consortium organized different activities in support of students and young professionals during the global health crisis. Despite the challenges and necessary adjustments, the unprecedented situation helped the organization adapt to change and encouraged us to revisit our roles as an international organization. The ISPRS SC hosts and coordinates activities and events both in person and online, including the Webinar Series, the publication of the SpeCtrum and the summer schools. During the pandemic, we improved our existing activities to provide support to our members and to the scientific community in general as we navigate major lifestyle changes and become more adept in using technology in our day-to-day lives. We also introduced new initiatives such as the Virtual Rooms and the GeoMixer, and continued to work in partnership with different organizations in remote sensing, photogrammetry and spatial information science. Moreover, we continued to strengthen our connection to the ISPRS through a collaboration with the ISPRS White Elephant Club and for a special event honouring one of the most important figures in the Society and in the profession. With all these activities organized during this challenging time, the Consortium experienced growth in terms of organizing and improving its activities, our roles as an international organization, and our online presence. The Consortium has also taken steps for continuity and sustained relevance to both the youth and ISPRS

On occurrence of certain biotoxins along the Kerala Coast

Occurrence of algal blooms has been reported from the coastal regions of Kerala. A study was conducted to collect detailed information on location and seasonality of the incidence of PSP and DSP toxins in-the bivalves of (his region for providing advance warning to avoid shellfish poisoning. A database on the hydrographic parameters in relation to algal blooms and toxic blooms at selected stations, which are sites of frequent blooms in the past years, was prepared

Transition probabilities in the X(5) candidate 122^{122}Ba

To investigate the possible X(5) character of 122Ba, suggested by the ground state band energy pattern, the lifetimes of the lowest yrast states of 122Ba have been measured, via the Recoil Distance Doppler-Shift method. The relevant levels have been populated by using the 108Cd(16O,2n)122Ba and the 112Sn(13C,3n)122Ba reactions. The B(E2) values deduced in the present work are compared to the predictions of the X(5) model and to calculations performed in the framework of the IBA-1 and IBA-2 models

Handwritten Digits and Optical Characters Recognition

The process of transcribing a language represented in its spatial form of graphical characters into its symbolic representation is called handwriting recognition. Each script has a collection of characters or letters, often known as symbols, that all share the same fundamental shapes. Handwriting analysis aims to correctly identify input characters or images before being analysed by various automated process systems. Recent research in image processing demonstrates the significance of image content retrieval. Optical character recognition (OCR) systems can extract text from photographs and transform that text to ASCII text. OCR is beneficial and essential in many applications, such as information retrieval systems and digital libraries